Abstract

Computational approaches have been increasingly applied to drug design over the past three decades and have already provided some useful results in the discovery of anticancer drugs. Given the increased availability of crystal structures in recent years, a growing number of molecular modeling studies on tubulin have been reported. Herein we present a brief overview of the role played by computational methods in anti-tubulin research, specifically in the context of colchicine binding agent research. An overview of current structures is reported, along with a brief discussion on the issues associated with the various tubulin isotypes. Finally, a summary of the most recent and relevant results is presented, highlighting the challenges and opportunities faced by researchers in this field.

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